A study on feature analysis for musical instrument classification.
Identifieur interne : 001821 ( Main/Exploration ); précédent : 001820; suivant : 001822A study on feature analysis for musical instrument classification.
Auteurs : Jeremiah D. Deng [Nouvelle-Zélande] ; Christian Simmermacher ; Stephen CranefieldSource :
- IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society [ 1083-4419 ] ; 2008.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
In tackling data mining and pattern recognition tasks, finding a compact but effective set of features has often been found to be a crucial step in the overall problem-solving process. In this paper, we present an empirical study on feature analysis for recognition of classical instrument, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes. It is revealed that there is significant redundancy between and within feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary in order to optimize feature selection and achieve better results for the instrument recognition problem.
DOI: 10.1109/TSMCB.2007.913394
PubMed: 18348925
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A study on feature analysis for musical instrument classification.</title><author><name sortKey="Deng, Jeremiah D" sort="Deng, Jeremiah D" uniqKey="Deng J" first="Jeremiah D" last="Deng">Jeremiah D. Deng</name><affiliation wicri:level="1"><nlm:affiliation>Department of Information Science, University of Otago, Dunedin, New Zealand. ddeng@infoscience.otago.ac.nz</nlm:affiliation><country xml:lang="fr">Nouvelle-Zélande</country><wicri:regionArea>Department of Information Science, University of Otago, Dunedin</wicri:regionArea><wicri:noRegion>Dunedin</wicri:noRegion></affiliation></author><author><name sortKey="Simmermacher, Christian" sort="Simmermacher, Christian" uniqKey="Simmermacher C" first="Christian" last="Simmermacher">Christian Simmermacher</name></author><author><name sortKey="Cranefield, Stephen" sort="Cranefield, Stephen" uniqKey="Cranefield S" first="Stephen" last="Cranefield">Stephen Cranefield</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2008">2008</date><idno type="RBID">pubmed:18348925</idno><idno type="pmid">18348925</idno><idno type="doi">10.1109/TSMCB.2007.913394</idno><idno type="wicri:Area/Main/Corpus">001797</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">001797</idno><idno type="wicri:Area/Main/Curation">001797</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">001797</idno><idno type="wicri:Area/Main/Exploration">001797</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A study on feature analysis for musical instrument classification.</title><author><name sortKey="Deng, Jeremiah D" sort="Deng, Jeremiah D" uniqKey="Deng J" first="Jeremiah D" last="Deng">Jeremiah D. Deng</name><affiliation wicri:level="1"><nlm:affiliation>Department of Information Science, University of Otago, Dunedin, New Zealand. ddeng@infoscience.otago.ac.nz</nlm:affiliation><country xml:lang="fr">Nouvelle-Zélande</country><wicri:regionArea>Department of Information Science, University of Otago, Dunedin</wicri:regionArea><wicri:noRegion>Dunedin</wicri:noRegion></affiliation></author><author><name sortKey="Simmermacher, Christian" sort="Simmermacher, Christian" uniqKey="Simmermacher C" first="Christian" last="Simmermacher">Christian Simmermacher</name></author><author><name sortKey="Cranefield, Stephen" sort="Cranefield, Stephen" uniqKey="Cranefield S" first="Stephen" last="Cranefield">Stephen Cranefield</name></author></analytic><series><title level="j">IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society</title><idno type="ISSN">1083-4419</idno><imprint><date when="2008" type="published">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms (MeSH)</term><term>Artificial Intelligence (MeSH)</term><term>Decision Support Techniques (MeSH)</term><term>Equipment Failure Analysis (MeSH)</term><term>Information Storage and Retrieval (methods)</term><term>Music (MeSH)</term><term>Pattern Recognition, Automated (methods)</term><term>Sound Spectrography (methods)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes (MeSH)</term><term>Analyse de panne d'appareillage (MeSH)</term><term>Intelligence artificielle (MeSH)</term><term>Musique (MeSH)</term><term>Mémorisation et recherche des informations (méthodes)</term><term>Reconnaissance automatique des formes (méthodes)</term><term>Spectrographie sonore (méthodes)</term><term>Techniques d'aide à la décision (MeSH)</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Information Storage and Retrieval</term><term>Pattern Recognition, Automated</term><term>Sound Spectrography</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Mémorisation et recherche des informations</term><term>Reconnaissance automatique des formes</term><term>Spectrographie sonore</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Artificial Intelligence</term><term>Decision Support Techniques</term><term>Equipment Failure Analysis</term><term>Music</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Analyse de panne d'appareillage</term><term>Intelligence artificielle</term><term>Musique</term><term>Techniques d'aide à la décision</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In tackling data mining and pattern recognition tasks, finding a compact but effective set of features has often been found to be a crucial step in the overall problem-solving process. In this paper, we present an empirical study on feature analysis for recognition of classical instrument, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes. It is revealed that there is significant redundancy between and within feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary in order to optimize feature selection and achieve better results for the instrument recognition problem.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">18348925</PMID><DateCompleted><Year>2008</Year><Month>05</Month><Day>06</Day></DateCompleted><DateRevised><Year>2008</Year><Month>03</Month><Day>19</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1083-4419</ISSN><JournalIssue CitedMedium="Print"><Volume>38</Volume><Issue>2</Issue><PubDate><Year>2008</Year><Month>Apr</Month></PubDate></JournalIssue><Title>IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society</Title><ISOAbbreviation>IEEE Trans Syst Man Cybern B Cybern</ISOAbbreviation></Journal><ArticleTitle>A study on feature analysis for musical instrument classification.</ArticleTitle><Pagination><MedlinePgn>429-38</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1109/TSMCB.2007.913394</ELocationID><Abstract><AbstractText>In tackling data mining and pattern recognition tasks, finding a compact but effective set of features has often been found to be a crucial step in the overall problem-solving process. In this paper, we present an empirical study on feature analysis for recognition of classical instrument, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes. It is revealed that there is significant redundancy between and within feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary in order to optimize feature selection and achieve better results for the instrument recognition problem.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Deng</LastName><ForeName>Jeremiah D</ForeName><Initials>JD</Initials><AffiliationInfo><Affiliation>Department of Information Science, University of Otago, Dunedin, New Zealand. ddeng@infoscience.otago.ac.nz</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Simmermacher</LastName><ForeName>Christian</ForeName><Initials>C</Initials></Author><Author ValidYN="Y"><LastName>Cranefield</LastName><ForeName>Stephen</ForeName><Initials>S</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>IEEE Trans Syst Man Cybern B Cybern</MedlineTA><NlmUniqueID>9890044</NlmUniqueID><ISSNLinking>1083-4419</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="Y">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001185" MajorTopicYN="Y">Artificial Intelligence</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003661" MajorTopicYN="Y">Decision Support Techniques</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019544" MajorTopicYN="N">Equipment Failure Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016247" MajorTopicYN="N">Information Storage and Retrieval</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D009146" MajorTopicYN="Y">Music</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010363" MajorTopicYN="N">Pattern Recognition, Automated</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013018" MajorTopicYN="N">Sound Spectrography</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2008</Year><Month>3</Month><Day>20</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2008</Year><Month>5</Month><Day>7</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2008</Year><Month>3</Month><Day>20</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">18348925</ArticleId><ArticleId IdType="doi">10.1109/TSMCB.2007.913394</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Nouvelle-Zélande</li></country></list><tree><noCountry><name sortKey="Cranefield, Stephen" sort="Cranefield, Stephen" uniqKey="Cranefield S" first="Stephen" last="Cranefield">Stephen Cranefield</name><name sortKey="Simmermacher, Christian" sort="Simmermacher, Christian" uniqKey="Simmermacher C" first="Christian" last="Simmermacher">Christian Simmermacher</name></noCountry><country name="Nouvelle-Zélande"><noRegion><name sortKey="Deng, Jeremiah D" sort="Deng, Jeremiah D" uniqKey="Deng J" first="Jeremiah D" last="Deng">Jeremiah D. Deng</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/SanteMusiqueV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001821 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 001821 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= SanteMusiqueV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:18348925
|texte= A study on feature analysis for musical instrument classification.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:18348925" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a SanteMusiqueV1
| This area was generated with Dilib version V0.6.38. |  |